Computer-based link analysis is increasingly used in law enforcement investigations, insurance fraud detection, telecommunications network analysis, pharmaceuticals research, epidemiology, and a host of other specialized applications. Link analysis explores associations among large numbers of objects of different types. For example, a law enforcement application might examine familial relationships among suspects and victims, the addresses at which those persons reside, and the telephone numbers that they called during a specified period. The ability of link analysis to represent relationships and associations among objects of different types has proven crucial in assisting human investigators to comprehend complex webs of evidence and draw conclusions that are not apparent from any single piece of information. However, there is both a need and opportunity to apply new technologies. Much of the current software for link analysis is little more than a graphical display tool. While visualizing networks has proven useful, some advanced applications of link analysis involve tens of thousands of objects and links as well as a rich array of possible data models. Manual construction and analysis of such networks has proven difficult. In addition, a large number of related techniques in artificial intelligence and several other fields have the potential to assist human reasoning about complex networks of relationships. These techniques draw on work from search, semantic networks, ontological engineering, autonomous agents, inductive logic programming, graph theory, social network analysis, knowledge discovery in databases, entity-relationship modeling, information extraction, information retrieval, and metaphor.